firasd

Across the four analytical choices, analysts went with their agent’s lean 86% of the time. If the agent’s input made no difference, we’d expect about 50%. "

People are just so used to the chat style APIs that they didn't even consider doing things like sending a bunch of emojis to a chat model and then asking for the optimal one in this context etc. Also chat models are pricier for the same behavior and can also output something random like a refusal

But yeah ironically I think in the initial breakthrough LLM paper on GPT-3 in 2020 some of the multiple choice questions were answered by comparing token probabilities of specific continuations rather than fill in the blank

For example, it's not an accident that software development is a very 'open' industry. You can learn anything about making a NextJS shopping cart online. Because nobody is really getting value by holding this knowledge as secret 'alpha'

On the flipside for example, academics, scientists and journalists often have very different incentives. Getting the credit for being the first to talk about an issue is what matters for their career so they are likely to be guarded about what they're working on or what their methods are

And this is why Zuck open sources LLMs; he is not really selling tokens in some infra service so keeping the output generation scarce doesn't really matter to Meta

(Joel Spolsky had an adjacent idea saying "Smart companies try to commoditize their products’ complements" like Billboard publishes a lot of music journalism for free but monetizes their chats/data)

Anyway, so this explains what's going on with this electronics retailer--while it is still a perspective and effort that is uncommon--publishing the schematic is not competitive with the shop unless you start manufacturing and open up another shop

And on the flipside a lot of AI vendor ideas like helping doctors turn voice transcripts into notes has just been annoying for the prospective user--they feel they may as well type it up themselves if they then have to review and correct the AI notes

There are definitely guys in some companies just pointing an agent swarm at 50 Github tickets and saying "go get 'em boys" and hence need a lot of orchestration tools but for the rest of us do we really need the AI to do all the build steps and the testing steps... or do we just need the new feature that runs when the button is clicked and then we can check it out in the browser ourselves. The code gen is what I need the AI for, not the 'smoke tests' and the tsc finagling. I'm willing to spend some mental calories myself in figuring this feature out step by step

Actually this makes me wonder if some people are just not very into building step by step like "okay first let's check the JSON shape the endpoint returns", "okay now let's make a simple form", etc

So to a large extent this has been mitigated and not using the suggestion here, which is to create a permanent URL ontology upfront

That said eventually neglect, removal, reorgs (or simply websites going offline) still happens... but the way the suggested goal has been advanced is due to becoming a business priority and with redirects and CMSes as tech to help

That said one suggestion made here turned out to be very useful and indeed is the default in WP:

   http://www.w3.org/1998/12/01/chairs

> A reason for using a topic area as part of the URI is that responsibility for sub-parts of a URI space is typically delegated, and then you need a name for the organizational body - the subdivision or group or whatever - which has responsibility for that sub-space. This is binding your URIs to the organizational structure. It is typically safe only when protected by a date further up the URI (to the left of it): 1998/pics can be taken to mean for your server "what we meant in 1998 by pics", rather than "what in 1998 we did with what we now refer to as pics."

I may be wrong! But I am definitely giving such claims the side-eye

But there is a clear line that gets crossed if you start actually making a database of millions of synthetic users and that's what happened with 'Frank' that sold to JP Morgan and eventually the founder was prosecuted

App store fees is a much more obvious example of something subject to regulatory scrutiny vs what much of what Biden's FTC under Lina Khan was working on.

So yeah there is a weird pass this company gets

Is there astrology in this app? No. Was there..? Yes. And the person complaining skipped mentioning that detail about their app

But I guess the point is that even in the MySQL scenario the 'reserved_quantities' is almost like a temporary table so either way is not the 'Real' inventory

I’ve wondered for a while if they could be used as an extension to your laptop like the old 80s PCs where you would plug in hardware.

So ‘make it a server’ is the obvious way I guess, and then you could do things like render webpages on there and then stream them as images to your actual computer (like the now shutdown Mighty app), or run ffmpeg on there to convert a video, etc

Meanwhile on LinkedIn if you post your thoughts on something, share an article, or mention a project they give you a good push to at least a few dozen people and you may see a like or two from a 3rd degree contact(!) within minutes. And then they aggressively SEO the feed too so now if someone Googles your name your LinkedIn posts will show up

Looks like on <https://arena.ai> agent arena (grouped by lab) Nvidia is 15/15 (much worse than Thinky and Mistral) and on text arena it's 18/27

On <https://openrouter.ai/models?order=most-popular> I definitely see usage though (probably mostly cause Nemotron 3 Ultra is free) the grouped order is DeepSeek, Tencent, Xiaomi, OpenAI, Z.ai, Nvidia

Ah but Mira Murati's new Inkling is Apache 2.0

But it makes sense that if you're a university researcher you are thinking about what's a model that will be open weight and developed over the long term and doesn't raise 'Chyna' concerns in Washington DC

So building is faster, but marketing—not so much

Alphadec is just a timezone free UTC encoding that works down the millisecond so I also use it for snapshots eg

  myscript.py.backup.2026_P5G6_328054_Aug06.txt

A clock is, at its core, a marriage of two components: a mechanism that oscillates, or ticks with a steady beat, and a device that counts those beats and displays the time

Yeah but more deeply time is a property of the universe that the clock including atomic clocks are tracking. Kant said it is 'schema' i.e. without understanding time we wouldn't even understand causality so it is the purest possible a-priori concept that doesn't rely on sensory input to learn about

This is why I like using my Alphadec system that splits the year into 26 chunks from A-Z <https://github.com/firasd/alphadec> as my working dir; eg. right now the current Alphadec is '2026_P5M7_200286' so my working dir is Documents/work/2026_P. That way there is a folder system automatically imposed on various .js or .py stuff without having to pre-create a taxonomy since 'time is schema'--I can estimate "that ffmpeg project was in Spring so it must be around 2026_F.."